基于DEA-Malmquist模型的西北地区能源空间转运格局效率及其变化分析
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摘要
西北地区有着丰富的能源资源,对其能源空间转运格局进行效率评价及全要素生产率时空演变分析,对推动整个地区的发展有着重要意义.运用DEA中的BCC模型,对2016年西北地区的铁路和公路货运效率进行研究.利用Malmquist指数方法及ArcGIS软件,进一步分析2010-2016年西北地区铁路、公路货运全要素生产率的时空演变和地区差异.研究表明:1)2016年西北地区铁路货运效率总体水平较高,公路中等;存在地区差异性,东部整体高于西部;规模效率决定其有效性.2) 2010-2016年铁路和公路的Malmquist指数整体较稳定,技术进步变化对该指数影响最大.从时空演变来看,2010-2016西北地区铁路货运的Malmquist指数先升后降,地区差异先减小后增大;公路货运的Malmquist指数先降后升,地区差异先减小后增大最后又减小.
As there are abundant energy resources in Northwest China, the efficiency evaluation of its energy space transfer pattern and the analysis of the spatial-temporal evolution of total factor productivity(TFP) are of great significance to the development of the entire region. Using the BCC model of DEA method, the efficiency of railway and highway freight transport in the northwestern region in 2016 was evaluated. With Malmquist index method and ArcGIS software, further analyze was put on the spatial-temporal evolution and regional differences of TFP of railway and highway freight transport in northwest China from 2010 to 2016. The research shows that: 1) In 2016, the overall efficiency of railway freight transportation in Northwest China was high, while the highway was medium; there was a certain regional difference, and the eastern region was higher than the western; Scale efficiency determines its effectiveness. 2) TFP index of railways and highways was generally stable from2010 to 2016, and changes in technological progress had the greatest impact on the index.In terms of the spatial-temporal evolution, TFP index of railway freight in Northwest China rose first and then decreased from 2010 to 2016. Regional differences decreased first and then increased; TFP index of highway freight fell first and then increased, and the regional differences decreased first, then increased and decreased finally.
As there are abundant energy resources in Northwest China, the efficiency evaluation of its energy space transfer pattern and the analysis of the spatial-temporal evolution of total factor productivity(TFP) are of great significance to the development of the entire region. Using the BCC model of DEA method, the efficiency of railway and highway freight transport in the northwestern region in 2016 was evaluated. With Malmquist index method and ArcGIS software, further analyze was put on the spatial-temporal evolution and regional differences of TFP of railway and highway freight transport in northwest China from 2010 to 2016. The research shows that: 1) In 2016, the overall efficiency of railway freight transportation in Northwest China was high, while the highway was medium; there was a certain regional difference, and the eastern region was higher than the western; Scale efficiency determines its effectiveness. 2) TFP index of railways and highways was generally stable from2010 to 2016, and changes in technological progress had the greatest impact on the index.In terms of the spatial-temporal evolution, TFP index of railway freight in Northwest China rose first and then decreased from 2010 to 2016. Regional differences decreased first and then increased; TFP index of highway freight fell first and then increased, and the regional differences decreased first, then increased and decreased finally.
引文
[1]邹才能,赵群,张国生,熊波.能源革命:从化石能源到新能源[J].天然气工业,2016, 36(1):1-10.
[2]姜广君.我国能源运输通道体系综合评价及优化研究[D].中国矿业大学(北京),2011.
[3] Costa. Evaluation public transport efficiency with neural network models[J]. Transportation Research Part C, 1997, 5(5):301-312.
[4] Fielding G J, Glauthier R E, Lave C A. Performance indicatiors for transit management[J]. Transportation, 1978, 7(4):365-379.
[5] Gilbert G, Dajani J. Measuring the performance of transit service[M]. Chapel Hill, North Carolina:University of North Carolina Press, 1975.
[6] Levinson D. Perspectives on efficiency in transportation[J]. International Journal of Transport Management, 2003, 1(3):145-155.
[7] Karlaftis M G, Tsamboulas D. Efficiency measurement inpublic transport:Are findings specification sensitive?[J]. Transportation Research Part A:Policy and Practice, 2012, 46(2):392-402.
[8] Jain P, Cullinane S, Cullinane K. The impact of governancedevelopment models on urban rail efficiency[J]. Transportation Research Part A:Policy and Practice, 2008, 42(9):1238-1250.
[9]吴威,曹有挥,梁双波.运输效率研究述评及基于交通运输地理学视角的研究展望[J].地理科学进展,2013, 32(2):243-250.
[10]鲍星星,陈森发.基于DEA的交叉效率模型在交通运输评价中的应用[J].东南大学学报(哲学社会科学版),2009, 11(S2):23-25.
[11]段新,岑晏青,路敖青.基于DEA模型的31省份公路运输效率分析[J].交通运输系统工程与信息,2011, 11(6):25-29.
[12]李洁,左毅刚.基于超效率DEA方法的公路运输效率评价与分析[J].交通信息与安全,2015, 33(1):127-132.
[13]张璐璐,吴威,刘斌全.基于DEA-Malmquist指数的长江三角洲地区公路交通运输效率评价与分析[J].中国科学院大学学报,2017, 34(6):712-718.
[14]谭玉顺,陈森发.中国铁路运输效率研究——基于网络DEA-RAM模型的视角[J].铁道科学与工程学报,2015, 12(5):1219-1226.
[15]仲维庆.基于DEA-C~2R模型的区域交通运输协调效率分析[J].哈尔滨商业大学学报(社会科学版),2014(4):60-64.
[16]王贺封,石忆邵,尹昌应.基于DEA模型和Malmquist生产率指数的上海市开发区用地效率及其变化[J].地理研究,2014, 33(9):1636-1646.
[17]赵林,张宇硕,焦新颖,吴迪,吴殿廷.基于SBM和Malmquist生产率指数的中国海洋经济效率评价研究[J].资源科学,2016, 38(3):461-475.
[18]杨清可,段学军.基于DEA-Malmquist模型的高新技术产业发展效率的时空测度与省际差异研究[J].经济地理,2014, 34(7):103-110.
[19]李守林,赵瑞,陈丽华.基于DEA-Malmquist指数的交通运输上市企业动态效率实证分析[J].中国流通经济,2017, 31(12):92-100.
[20]胡宗彪,朱明进.中国流通服务业生产率的部门及区域差异研究[J].山西财经大学学报,2016, 38(8):35-45.
[2]姜广君.我国能源运输通道体系综合评价及优化研究[D].中国矿业大学(北京),2011.
[3] Costa. Evaluation public transport efficiency with neural network models[J]. Transportation Research Part C, 1997, 5(5):301-312.
[4] Fielding G J, Glauthier R E, Lave C A. Performance indicatiors for transit management[J]. Transportation, 1978, 7(4):365-379.
[5] Gilbert G, Dajani J. Measuring the performance of transit service[M]. Chapel Hill, North Carolina:University of North Carolina Press, 1975.
[6] Levinson D. Perspectives on efficiency in transportation[J]. International Journal of Transport Management, 2003, 1(3):145-155.
[7] Karlaftis M G, Tsamboulas D. Efficiency measurement inpublic transport:Are findings specification sensitive?[J]. Transportation Research Part A:Policy and Practice, 2012, 46(2):392-402.
[8] Jain P, Cullinane S, Cullinane K. The impact of governancedevelopment models on urban rail efficiency[J]. Transportation Research Part A:Policy and Practice, 2008, 42(9):1238-1250.
[9]吴威,曹有挥,梁双波.运输效率研究述评及基于交通运输地理学视角的研究展望[J].地理科学进展,2013, 32(2):243-250.
[10]鲍星星,陈森发.基于DEA的交叉效率模型在交通运输评价中的应用[J].东南大学学报(哲学社会科学版),2009, 11(S2):23-25.
[11]段新,岑晏青,路敖青.基于DEA模型的31省份公路运输效率分析[J].交通运输系统工程与信息,2011, 11(6):25-29.
[12]李洁,左毅刚.基于超效率DEA方法的公路运输效率评价与分析[J].交通信息与安全,2015, 33(1):127-132.
[13]张璐璐,吴威,刘斌全.基于DEA-Malmquist指数的长江三角洲地区公路交通运输效率评价与分析[J].中国科学院大学学报,2017, 34(6):712-718.
[14]谭玉顺,陈森发.中国铁路运输效率研究——基于网络DEA-RAM模型的视角[J].铁道科学与工程学报,2015, 12(5):1219-1226.
[15]仲维庆.基于DEA-C~2R模型的区域交通运输协调效率分析[J].哈尔滨商业大学学报(社会科学版),2014(4):60-64.
[16]王贺封,石忆邵,尹昌应.基于DEA模型和Malmquist生产率指数的上海市开发区用地效率及其变化[J].地理研究,2014, 33(9):1636-1646.
[17]赵林,张宇硕,焦新颖,吴迪,吴殿廷.基于SBM和Malmquist生产率指数的中国海洋经济效率评价研究[J].资源科学,2016, 38(3):461-475.
[18]杨清可,段学军.基于DEA-Malmquist模型的高新技术产业发展效率的时空测度与省际差异研究[J].经济地理,2014, 34(7):103-110.
[19]李守林,赵瑞,陈丽华.基于DEA-Malmquist指数的交通运输上市企业动态效率实证分析[J].中国流通经济,2017, 31(12):92-100.
[20]胡宗彪,朱明进.中国流通服务业生产率的部门及区域差异研究[J].山西财经大学学报,2016, 38(8):35-45.